Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 5:00 PM ET (12:00 - 21:00 UTC). We apologize for the inconvenience.
By Topic

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on

Issue 4 • Date Aug 1997

Filter Results

Displaying Results 1 - 19 of 19
  • On typical values and fuzzy integrals

    Publication Year: 1997 , Page(s): 703 - 705
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (116 KB)  

    A new approach for obtaining a typical value of a fuzzy set as a fuzzy integral is developed by replacing the classic Lebesgue measure with the “typicality” measure. A new method for representing and calculating the one-dimensional fuzzy integral with respect to arbitrary measure derived by monotonic increasing function is proposed and its applicability is illustrated with examples View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Interval-valued fuzzy hypergraph and fuzzy partition

    Publication Year: 1997 , Page(s): 725 - 733
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB)  

    This paper extends the work of H. Lee-Kwang and L.M. Lee (1995) to present the concept of the interval-valued fuzzy hypergraph. In the interval-valued fuzzy hypergraph, the concepts of the dual interval-valued fuzzy hypergraph, the crisp-valued α-cut hypergraph, and the interval-valued [α12 ]-cut at β level hypergraph are developed, where α∈ [0, 1], 0⩽α1⩽α2⩽1, and β∈ [0, 1]. We also use some examples to show that the proposed concepts are useful for the analysis and fuzzy partition of a system View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Stochastic searching on the line and its applications to parameter learning in nonlinear optimization

    Publication Year: 1997 , Page(s): 733 - 739
    Cited by:  Papers (12)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (204 KB)  

    We consider the problem of a learning mechanism (for example, a robot) locating a point on a line when it is interacting with a random environment which essentially informs it, possibly erroneously, which way it should move. In this paper we present a novel scheme by which the point can he learned using some recently devised learning principles. The heart of the strategy involves discretizing the space and performing a controlled random walk on this space. The scheme is shown to be ε-optimal and to converge with probability 1. Although the problem is solved in its generality, its application in nonlinear optimization has also been suggested. Typically, an optimization process involves working one's way toward the maximum (minimum) using the local information that is available. However, the crucial issue in these strategies is that of determining the parameter to be used in the optimization itself. If the parameter is too small the convergence is sluggish. On the other hand, if the parameter is too large, the system could erroneously converge or even oscillate. Our strategy can be used to determine the best parameter to be used in the optimization View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • An adaptive neural fuzzy filter and its applications

    Publication Year: 1997 , Page(s): 635 - 656
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (680 KB)  

    A new kind of nonlinear adaptive filter, the adaptive neural fuzzy filter (ANFF), based upon a neural network's learning ability and fuzzy if-then rule structure, is proposed in this paper. The ANFF is inherently a feedforward multilayered connectionist network which can learn by itself according to numerical training data or expert knowledge represented by fuzzy if-then rules. The adaptation here includes the construction of fuzzy if-then rules (structure learning), and the tuning of the free parameters of membership functions (parameter learning). In the structure learning phase, fuzzy rules are found based on the matching of input-output clusters. In the parameter learning phase, a backpropagation-like adaptation algorithm is developed to minimize the output error. There are no hidden nodes (i.e., no membership functions and fuzzy rules) initially, and both the structure learning and parameter learning are performed concurrently as the adaptation proceeds. However, if some linguistic information about the design of the filter is available, such knowledge can be put into the ANFF to form an initial structure with hidden nodes. Two major advantages of the ANFF can thus be seen: 1) a priori knowledge can be incorporated into the ANFF which makes the fusion of numerical data and linguistic information in the filter possible; and 2) no predetermination, like the number of hidden nodes, must be given, since the ANFF can find its optimal structure and parameters automatically View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Sensor explication: knowledge-based robotic plan execution through logical objects

    Publication Year: 1997 , Page(s): 611 - 625
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB)  

    Complex robot tasks are usually described as high level goals, with no details on how to achieve them. However, details must be provided to generate primitive commands to control a real robot. A sensor explication concept that makes details explicit from general commands is presented. We show how the transformation from high-level goals to primitive commands can be performed at execution time and we propose an architecture based on reconfigurable objects that contain domain knowledge and knowledge about the sensors and actuators available. Our approach is based on two premises: 1) plan execution is an information gathering process where determining what information is relevant is a great part of the process; and 2) plan execution requires that many details are made explicit. We show how our approach is used in solving the task of moving a robot to and through an unknown, and possibly narrow, doorway; where sonic range data is used to find the doorway, walls, and obstacles. We illustrate the difficulty of such a task using data from a large number of experiments we conducted with a real mobile robot. The laboratory results illustrate how the proper application of knowledge in the integration and utilization of sensors and actuators increases the robustness of plan execution View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Learning control algorithms for tracking “slowly” varying trajectories

    Publication Year: 1997 , Page(s): 657 - 670
    Cited by:  Papers (25)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (736 KB)  

    To date, most of the available results in learning control have been utilized in applications where a robot is required to execute the same motion over and over again, with a certain periodicity. This is due to the requirement that all learning algorithms assume that a desired output is given a priori over the time duration t ∈ [0,T]. For applications where the desired outputs are assumed to change “slowly”, we present a D-type, PD-type, and PID-type learning algorithms. At each iteration we assume that the system outputs and desired trajectories are contaminated with measurement noise, the system state contains disturbances, and errors are present during reinitialization. These algorithms are shown to be robust and convergent under certain conditions. In theory, the uniform convergence of learning algorithms is achieved as the number of iterations tends to infinity. However, in practice we desire to stop the process after a minimum number of iterations such that the trajectory errors are less than a desired tolerance bound. We present a methodology which is devoted to alleviate the difficulty of determining a priori the controller parameters such that the speed of convergence is improved. In particular, for systems with the property that the product matrix of the input and output coupling matrices, CB, is not full rank. Numerical examples are given to illustrate the results View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A new approach to adaptive fuzzy control: the controller output error method

    Publication Year: 1997 , Page(s): 686 - 691
    Cited by:  Papers (22)  |  Patents (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (176 KB)  

    The controller output error method (COEM) is introduced and applied to the design of adaptive fuzzy control systems. The method employs a gradient descent algorithm to minimize a cost function which is based on the error at the controller output. This contrasts with more conventional methods which use the error at the plant output. The cost function is minimized by adapting some or all of the parameters of the fuzzy controller. The proposed adaptive fuzzy controller is applied to the adaptive control of a nonlinear plant and is shown to be capable of providing good overall system performance View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A robust fuzzy logic controller for robot manipulators with uncertainties

    Publication Year: 1997 , Page(s): 706 - 713
    Cited by:  Papers (22)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (352 KB)  

    Owing to load variation and unmodeled dynamics, a robot manipulator can be classified as a nonlinear dynamic system with structured and unstructured uncertainties. In this paper, the stability and robustness of a class of the fuzzy logic control (FLC) is investigated and a robust FLC is proposed for a robot manipulator with uncertainties. In order to show the performance of the proposed control algorithm, computer simulations are carried out on a simple two-link robot manipulator View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Function approximation using fuzzy neural networks with robust learning algorithm

    Publication Year: 1997 , Page(s): 740 - 747
    Cited by:  Papers (60)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (304 KB)  

    The paper describes a novel application of the B-spline membership functions (BMF's) and the fuzzy neural network to the function approximation with outliers in training data. According to the robust objective function, we use gradient descent method to derive the new learning rules of the weighting values and BMF's of the fuzzy neural network for robust function approximation. In this paper, the robust learning algorithm is derived. During the learning process, the robust objective function comes into effect and the approximated function will gradually be unaffected by the erroneous training data. As a result, the robust function approximation can rapidly converge to the desired tolerable error scope. In other words, the learning iterations will decrease greatly. We realize the function approximation not only in one dimension (curves), but also in two dimension (surfaces). Several examples are simulated in order to confirm the efficiency and feasibility of the proposed approach in this paper View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A note on “Solving the find-path problem by good representation of free space”

    Publication Year: 1997 , Page(s): 723 - 724
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (84 KB)  

    The conditions of a pure translation and a pure rotation for car-like robots and dual-drive robots are derived. Based on these conditions the suitability of the path planning algorithm developed by R.A Brooks (1983) for each of the two kinds of mobile robots is discussed View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A counterexample to the Alexopoulos-Griffin path planning algorithm

    Publication Year: 1997 , Page(s): 721 - 723
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (116 KB)  

    The planar stationary-obstacle path-planning problem for polygonal obstacles has been correctly and completely solved by T. Lozano-Perez and M. Wesley (1979), i.e., a global, optimal algorithm was provided which requires O(μ2logμ) computation time, where μ is the number of obstacle-faces in the scene. That algorithm is known as the VGRAPH algorithm. Two variants of VGRAPH have been developed to solve the same problem in O(μ2) computation time. Our paper discusses a recent algorithm proposed by C. Alexopoulos and P.M. Griffin (1992), called V*GRAPH, which also claims to provide an optimal solution. We demonstrate by counter-example that V*GRAPH is neither global nor optimal View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A traffic priority language for collision-free navigation of autonomous mobile robots in dynamic environments

    Publication Year: 1997 , Page(s): 573 - 587
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (548 KB)  

    This paper presents a generic traffic priority language, called KYKLOFORTA, used by autonomous robots for collision-free navigation in a dynamic unknown or known navigation space. In a previous work by X. Grossmman (1988), a set of traffic control rules was developed for the navigation of the robots on the lines of a two-dimensional (2-D) grid and a control center coordinated and synchronized their movements. In this work, the robots are considered autonomous: they are moving anywhere and in any direction inside the free space, and there is no need of a central control to coordinate and synchronize them. The requirements for each robot are i) visual perception, ii) range sensors, and iii) the ability of each robot to detect other moving objects in the same free navigation space, define the other objects perceived size, their velocity and their directions. Based on these assumptions, a traffic priority language is needed for each robot, making it able to decide during the navigation and avoid possible collision with other moving objects. The traffic priority language proposed here is based on a set of primitive traffic priority alphabet and rules which compose pattern of corridors for the application of the traffic priority rules View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A reactive coordination scheme for a many-robot system

    Publication Year: 1997 , Page(s): 598 - 610
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (212 KB)  

    This paper presents a novel approach for coordinating a homogeneous system of mobile robots using implicit communication in the form of broadcasts. The broadcast-based coordination scheme was developed for the Army Ant swarm-a system of small, relatively inexpensive mobile robots that can accomplish complex tasks by cooperating as a team. The primary drawback, however, of the Army Ant system is that the absence of a central supervisor poses difficulty in the coordination and control of the agents. Our coordination scheme provides a global “group dynamic” that controls the actions of each robot using only local interactions. Coordination of the swarm is achieved with signals we call “heartbeats”. Each agent broadcasts a unique heartbeat and responds to the collective behavior of all other heartbeats. We generate heartbeats with van der Pol oscillators. In this application, we use the known properties of coupled van der Pol oscillators to create predictable group behavior. Some of the properties and behaviors of coupled van der Pol oscillators are discussed in detail. We emphasize the use of this scheme to allow agents to simultaneously perform an action such as lifting, steering, or changing speed. The results of experiments performed on three actual heartbeat circuits are presented and the behavior of the realized system is compared to simulated results. We also demonstrate the application of the coordination scheme to global speed control View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Algebraically structured colored Petri nets to model sequential processes

    Publication Year: 1997 , Page(s): 681 - 686
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (212 KB)  

    Sequential processes can hardly be modeled with Colored Petri Nets (CPN). Their standard functions (such as “Succ” and “Prec”) can only describe simple cases whereas modeling a complex sequence requires the definition of a function via a cumbersome and static table. In order to overcome these limitations, we first introduce a mixed structure based upon CPN and FIFO queues; then, we define an isomorphism between the set of colors and a finite field Z /pZ enabling symbolic calculation using polynomials associated with arcs instead of linear functions mapping sets into sets. Finally, several examples illustrate their modeling capabilities including failure recovery View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Nonlinear parameter estimation by weighted linear associative memory with nonzero interception

    Publication Year: 1997 , Page(s): 692 - 702
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (372 KB)  

    The method of linear associative memory (LAM) has recently been applied in nonlinear parameter estimation. In the method of LAM, a model response, nonlinear with respect to the parameters, is approximated linearly by a matrix, which maps inversely from a response vector to a parameter vector. This matrix is determined from a set of initial training parameter vectors and their response vectors according to a given cost function, and can be updated recursively and adaptively with a pair of newly generated parameter-response vector. The advantage of LAM is that it can yield good estimation of the true parameter from a given observed response even if the initial training parameter vectors are far from the true values. In a previous paper, we have significantly improved the LAM method by introducing a weighted linear associative memory (WLAM) approach for nonlinear parameter estimation. In the WLAM approach, the contribution of each pair of parameter-response vector to the cost function is weighted in a way such that if a response vector is closer to the observed one then its pair plays more important role in the cost function. However, in both LAM and WLAM, the linear association is introduced with zero interceptions, which would not give an exact association even if the model function is linear and so will affect the efficiency of the estimations. In this paper, we construct a theory which introduces a linear association memory with a nonzero interception (WLAMB). The results of our estimation tests on two quite different models, Van der Pol equation and somatic shunt cable model, suggest that WLAMB can still significantly improve on WLAM View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Design, control, and energetics of an electrically actuated legged robot

    Publication Year: 1997 , Page(s): 626 - 634
    Cited by:  Papers (48)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (200 KB)  

    To study the design, control and energetics of autonomous dynamically stable legged machines we have built a planar one-legged robot, the ARL Monopod. Its top running speed of 4.3 km/h (1.2 m/s) makes it the fastest electrically actuated legged robot to date. We adapted Raibert's control laws for the low power electric actuation necessary for autonomous locomotion and performed a detailed energetic analysis of our experiments. A comparison shows that the ARL Monopod with its 125 W average power consumption is more energy efficient than previously built robots View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Fuzzy query translation for relational database systems

    Publication Year: 1997 , Page(s): 714 - 721
    Cited by:  Papers (15)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (284 KB)  

    The paper presents a new method for fuzzy query translation based on the α-cuts operations of fuzzy numbers. This proposed method allows the retrieval conditions of SQL queries to be described by fuzzy terms represented by fuzzy numbers. It emphasizes friendliness and flexibility for inexperienced users. The authors have implemented a fuzzy query translator to translate user's fuzzy queries into precise queries for relational database systems. Because the proposed method allows the user to construct his fuzzy queries intuitively and to choose different retrieval threshold values for fuzzy query translation, the existing relational database systems will be more friendly and more flexible to the users View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Genetic-based search for error-correcting graph isomorphism

    Publication Year: 1997 , Page(s): 588 - 597
    Cited by:  Papers (16)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (248 KB)  

    Error-correcting graph isomorphism has been found useful in numerous pattern recognition applications. This paper presents a genetic-based search approach that adopts genetic algorithms as the searching criteria to solve the problem of error-correcting graph isomorphism. By applying genetic algorithms, some local search strategies are amalgamated to improve convergence speed. Besides, a selection operator is proposed to prevent premature convergence. The proposed approach has been implemented to verify its validity. Experimental results reveal the superiority of this new technique than several other well-known algorithms View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Database summarization using fuzzy ISA hierarchies

    Publication Year: 1997 , Page(s): 671 - 680
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (372 KB)  

    Summary discovery is one of the major components of knowledge discovery in databases, which provides the user with comprehensive information for grasping the essence from a large amount of information in a database. In this paper, we propose an interactive top-down summary discovery process which utilizes fuzzy ISA hierarchies as domain knowledge. We define a generalized tuple as a representational form of a database summary including fuzzy concepts. By virtue of fuzzy ISA hierarchies where fuzzy ISA relationships common in actual domains are naturally expressed, the discovery process comes up with more accurate database summaries. We also present an informativeness measure for distinguishing generalized tuples that delivers much information to users, based on Shannon's information theory View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.

Aims & Scope

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics focuses on cybernetics, including communication and control across humans, machines and organizations at the structural or neural level

 

This Transaction ceased production in 2012. The current retitled publication is IEEE Transactions on Cybernetics.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Eugene Santos, Jr.
Thayer School of Engineering
Dartmouth College